Effect of soaking conditions on glyphosate absorption in selected pulses: understanding solvent behaviour and morphological changes
Bibliographic record
Abstract
Pesticides are being used in agriculture in an unregulated and imprecise way, resulting in food grains having varying amounts of pesticide residues after harvest. Using farm samples to develop a new technique to determine the pesticide residue levels might result in inconsistent results. There is currently no specific technique for preparing the standard pulse samples with appropriate levels of glyphosate residual levels. The objective of this study was to develop a standard method for glyphosate spiking by evaluating the absorption of glyphosate in six types of pulses (chickpea, yellow pea, red lentil, large green lentil, French green lentil, and black beluga lentil) at four different concentrations (5 mg/kg, 10 mg/kg, 15 mg/kg and 20 mg/kg) using two different solvents (water and water + ethanol (50:50)). Both the type of pulse and nature of solvent significantly affected the glyphosate absorption. The highest glyphosate absorption as determined by ELISA was observed when water was used as solvent in all pulses and at all concentration levels. The values ranged from 3.45–17.46, 4.13–18.31, 4.08–17.09, 4.11–18.40, 4.99–18.43 and 4.56–18.04 mg/kg for yellow pea, chickpea, large green lentil, French green lentil, red lentil, and black beluga lentil, respectively. Among the pulses, the absorption was highest in red lentil and lowest in large green lentil, which can be attributed to their maximum moisture absorption capacity. Further, the colour changes were lower in water + ethanol solvent than water only probably due to the colour retention properties of ethanol. The results obtained with this technique showed the potential of preparing standard pulse samples with known glyphosate levels.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".